In 2008, a state-of-the-art driverless car could go two blocks on its own on a closed course at 25mph. By 2012, the driverless car could operate in real-world conditions at 75mph.

Such rapid progress offers great hope that the tremendous benefits in safety and savings I laid out in Part 1 of this series are attainable. The pace of progress also means that the disruptive ripple effects discussed in Part 2 might soon have strategic relevance for companies participating in the multi-trillion-dollar part of the economy that relates to cars. But we’re left with two crucial questions: How soon could the driverless car become a reality? When should incumbents, venture capitals and entrepreneurs start paying serious attention?

The short answer to both questions is: sooner than most think. This article explains why.

When estimating technology adoption, it is wise to remember Paul Saffo’s admonition to “never mistake a clear view for a short distance.” No matter how powerful a technology is, there are numerous factors that stand between technical viability and widespread adoption—cost, usability, customer acceptance, business models, entrenched interests, regulations and so on.

As illustrated in the figure, technology improves exponentially, but social, political and economic systems tend to change incrementally. Only when the differential between existing conditions and what is technically possible becomes large enough are human systems jolted into disruptive change. These jolts are the openings for “killer apps,” new goods or services that are so compelling that they catalyze a new generation of products. VisiCalc, the first spreadsheet, was the killer app for personal computers. , the first browser, was the killer app for the World Wide Web. The iPad was the killer app for tablets.

Let’s look at the adoption of the driverless car through the lens of the Law of Disruption, to see both how advanced the technology is and what social, political and economic systems might delay the “killer app” jolt.

Technology is the easy part. There’s ample evidence that driverless technology from and others is already better than many drivers. In addition to the riveting video of a 95%-blind man “driving” a Google car that I showed in Part 1 of this series, here’s a montage of on-the-road clips narrated by Chris Urmson, who currently leads Google’s driverless program.

As you absorb Chris’ description, keep in mind that his examples are almost two years old. The car’s progress has continued at the exponential rate illustrated in Figure 1 and will even accelerate once significant numbers of cars reach the road. That’s because, while we humans learn almost entirely from our own experiences, every Google car can learn from the experiences of every other Google car.

Blanketing the roads with Google cars will also provide incredibly detailed, up-to-the second information to the “cloud” about road conditions, traffic and travel times. Each car will draw on that information and know to be extra careful at dangerous intersections or know, say, that black ice was felt at a certain spot 15 minutes earlier.

With progress so rapid, the technology in the Google car has miles and miles of open road in front of it. Even skeptics seem to believe that the question about the timing of the driverless car is less “if” than “when.”

But the social, political and economic systems that could act as a limiting function on “when” are significant. Consider some of the commonly voiced hurdles: